Data compression is used in communications and computer networking to store, transmit, and reproduce information efficiently. It finds particular application in the encoding of images, audio and video. Common image compression formats include JPEG, TIFF, and PNG. A newly-developed video coding standard is the ITU-T H.265/HEVC standard. Other video coding formats include the VP8 and VP9 formats developed by Google Inc. Evolutions to all of these standards and formats are under active development.
All of these image and video coding standards and formats are based on predictive coding that create a prediction of data to be coded, then encode the error in the prediction (often called the residual) for transmission to a decoder as a bitstream. The decoder then makes the same prediction and adjusts it by the reconstructed error decoded from the bitstream. The data compression of the error at the encoder often includes a spectral transform of the error to create blocks of transform domain coefficients. This is typically accompanied by lossy quantization. The reverse operations are performed at the decoder to reconstruct the error/residual. Entropy coding (often context-adaptive) is typically used to encode the residual data, plus side information for making the predictions (e.g. intra-coding mode or inter-coding motion vectors), to generate a bitstream for transmission from encoder to decoder or for storage on a storage medium for later decoding. In some cases, the error at the encoder is encoded without using a spectral transform and/or quantization.
Recent developments in improving video coding performance have partly focused upon reducing the constraints on inter prediction, so that predictions may be may backwards, forwards, and may involve multiple reference pictures. This necessarily complicates the computational analysis in determining an optimal inter prediction at the encoder, and may necessitate an increase in the fast-access memory requirements at the decoder to perform the decoding process. As inter prediction has become increasingly more sophisticated and complex, it becomes increasingly clearer the returns in performance improvement are diminishing. Nevertheless, continued improvements in compression performance are sought by the video streaming and coding industries.
Similar reference numerals may have been used in different figures to denote similar components.